Older transgender women in Thailand: views of service providers

The social and cultural construction of aging and how it is experienced by transgender women in Thailand has been neglected within the academic literature. This qualitative study explored how Thai lesbian, gay, bisexual, transgender, and intersex (LGBTI) service providers construct aging transgender women. Fourteen semi-structured in-depth interviews and one focus group were conducted in Thailand between 2016 and 2017 with LGBTI staff members whose roles ranged from volunteer to senior management. This research was a part of a larger doctoral research project. In considering both gender identity and older age, a clearer understanding is established on how notions of “older” for transgender women are constructed by service providers. Thematic analysis was undertaken, which established that there is a lack of heterogeneity and shared understanding of the concepts of “age” and “older transgender women.” This key finding was compounded by the invisibility of older transgender women in the Thai landscape, which limited the extent to which older transgender women have been included in targeted service provision. Older transgender women lack agency and voice and have failed to be involved in the shaping of services that meet their needs.     

Exploring e-Mental Health Preferences of Generation Y

E-Mental Health services could substantially increase the capacity of the mental health care system. This article explores youth consumer preferences for online interventions targeting depression and anxiety. Twenty-three participants who had experienced suicidal ideation and either depression or anxiety and completed one qualitative interview were included. Interviews were topically guided to cover themes of e-Mental Health service preferences around online help-seeking behavior, appearance, content, privacy, and support. We found that youth positively received the idea of, and appreciated the need for, e-Mental Health services. Noted preferences for services were those that are simple to use, interactive, and include support through an online community.     

DPR Debate: Growth Identification and Facilitation: The Role of the State in the Dynamics of Structural Change

This DPR Debate is based on the contribution by Justin Lin, Chief Economist at the World Bank, and his colleague Célestin Monga, on ‘Growth Identification and Facilitation: The Role of the State in the Dynamics of Structural Change’. The article under consideration is important and timely as it articulates a number of new policy implications from Justin Lin's earlier work on New Structural Economics, which was discussed in a previous DPR debate (Lin and Chang, 2009). This symposium contains the article and comments on it from five distinguished specialists, and closes with a rejoinder by Lin and Monga. This introduction discusses the article, the comments and the rejoinder. The historical record indicates that, in all successful economies, the state has always played an important role in facilitating structural change and helping the private sector sustain it across time. This article puts forward a new approach to help policy‐makers in developing countries identify those industries that may hold latent comparative advantage, and recommends ways of removing binding constraints to facilitate private firms' entry into those industries. Two types of government interventions are distinguished: first, policies that facilitate structural change by overcoming information, co‐ordination and externality issues, which are intrinsic to industrial upgrading and diversification; and second, policies aimed at protecting certain selected firms and industries that defy the comparative advantage determined by the existing endowment structure.     

Civic capacity: Building on transformational leadership to explain successful integrative public leadership

An emerging stream of work has been investigating the leadership processes necessary to guide public multi-sector collaborations. This stream of work argues that new leadership theory about integrative public leadership is needed because the context is different from that traditionally investigated by leadership researchers. In this paper, we advance the study of integrative public leadership by arguing that transformational leadership theory does apply to multi-sector collaborations, but needs to be augmented with an additional construct called “civic capacity.” We elaborate on this construct and suggest that it consists of three components: civic drive, civic connections, and civic pragmatism.     

On Optimal Expediting Policy for Supply Systems with Uncertain Lead‐Times

We examine the role of expediting in dealing with lead‐time uncertainties associated with global supply chains of “functional products” (high volume, low demand uncertainty goods). In our developed stylized model, a retailer sources from a supplier with uncertain lead‐time to meet his stable and known demand, and the supply lead‐time is composed of two random duration stages. At the completion time of the first stage, the retailer has the option to expedite a portion of the replenishment order via an alternative faster supply mode. We characterize the optimal expediting policy in terms of if and how much of the order to expedite and explore comparative statics on the optimal policy to better understand the effects of changes in the cost parameters and lead‐time properties. We also study how the expediting option affects the retailer's decisions on the replenishment order (time and size of order placement). We observe that with the expediting option the retailer places larger orders closer to the start of the selling season, thus having this option serve as a substitute for the safety lead‐time and allowing him to take increased advantages of economies of scale. Finally we extend the basic model by looking at correlated lead‐time stages and more than two random lead‐time stages.     

A Simple Data Transformation for Estimating Benchmark Doses in Developmental Toxicity Experiments

Developmental anomalies induced by toxic chemicals may be identified using laboratory experiments with rats, mice or rabbits. Multinomial responses of fetuses from the same mother are often positively correlated, resulting in overdispersion relative to multinomial variation. In this article, a simple data transformation based on the concept of generalized design effects due to Rao-Scott is proposed for dose-response modeling of developmental toxicity. After scaling the original multinomial data using the average design effect, standard methods for analysis of uncorrected multinomial data can be applied. Benchmark doses derived using this approach are comparable to those obtained using generalized estimating equations with an extended Dirichlet-trinomial covariance function to describe the dispersion of the original data. This empirical agreement, coupled with a large sample theoretical justification of the Rao-Scott transformation, confirms the applicability of the statistical methods proposed in this article for developmental toxicity risk assessment.     

Combinatorial design of a minimum cost transfer line

The problem of equipment selection for a production line is considered. Each piece of equipment, also called unit or block, performs a set of operations. All necessary operations of the line and all available blocks with their costs are known. The difficulty is to choose the most appropriate blocks and group them into (work)stations. There are some constraints that restrict the assignment of different blocks to the same station. Two combinatorial approaches for solving this problem are suggested. Both are based on a novel concept of locally feasible stations. The first approach combinatorially enumerates all feasible solutions, and the second reduces the problem to search for a maximum weight clique. A boolean linear program based on a set packing formulation is presented. Computer experiments with benchmark data are described. Their results show that the set packing model is competitive and can be used to solve real-life problems.     

A robust branch-and-cut approach for the minimum-energy symmetric network connectivity problem

This paper considers the minimum-energy symmetric network connectivity problem (MESNC) in wireless sensor networks. The aim of the MESNC is to assign transmission power to each sensor node such that the resulting network, using only bidirectional links, is connected and the total energy consumption is minimized. We first present two new models of this problem and then propose new branch-and-cut algorithms. Based on an existing formulation, we present the first model by introducing additional constraints. These additional constraints allow us to relax certain binary variables to continuous ones and thus to reduce significantly the number of binary variables. Our second model strengthens the first one by adding an exponential number of lifted directed-connectivity constraints. We present two branch-and-cut procedures based on these proposed improvements. The computational results are reported and show that our approaches, using the proposed formulations, can efficiently solve instances with up to 120 nodes, which significantly improve our ability to solve much larger instances in comparison with other exact algorithms in the literature.     

Vector autoregression and causality: a theoretical overview and simulation study

This paper provides a theoretical overview of Wald tests for Granger causality in levels vector autoregressions (VAR's) and Johansen-type error correction models (ECM's). The theory is based on results in Toda and Phillips (1991a) and allows for stochastic and deterministic trends as well as arbitrary degrees of cointegration. We recommend some operational procedures for conducting Granger causality tests that are based on the Gaussian maximum likelihood estimation of ECM's. These procedures are applicable in the important practical case of testing the causal effects of one variable on another group of variables and vice versa. This paper also investigates the sampling properties of these testing procedures through simulation exercises. Three sequential causality tests in ECM's are compared with conventional causality tests in levels and differences VAR's.