Global Governance,neoliberalism and national responses: The case of Bangladesh’s ready‐made garment (RMG) sector

This article on the ready‐made garment (RMG) sector of Bangladesh shows how over‐reliance on foreign capital for development financing and deregulated investment—a hallmark of neoliberal economic arrangements—undermines the incorporation of SDGs’ and INGOs’ equity principles, contributing to biased policy responses yielding unequal outcomes. The article cautions that while countries prioritize economic growth over social and environmental nourishment and continue to adopt neoliberal economic policies to promote economic growth, inequity is unavoidable, if not inevitable. Thus, the way forward may be to shift the focus of ‘development’ from the economy to society, to building ‘good societies’ where institutions and strategies, including those that contribute to economic growth, are organized such that these complement not compromise the evolution of such societies.     

Global adjustment to US disengagement from the world trading system

US trade policy in the Trump administration is protectionist, raising tariffs outside of WTO rules, threatening trade wars, withdrawing from existing trade agreements, and negotiating new bilateral trade deals rather than free trade agreements. The reaction of the rest of the world has been to support the WTO rules-based trading system and to pursue new and expanded regional trade agreements that do not include the US. The result may be US disengagement from the world trading system, with countries diverting trade around the US. We use a global computable general equilibrium (CGE) model to analyze changes in trade and production patterns for a variety of scenarios, including US trade wars. We find that adjustment to US disengagement is feasible—the changes in trade shares as countries divert trade are modest and achievable, with very little impact on the volume of global trade. If the US engages in trade wars with major partners, the best response for other trade partners is to sit out the trade war, accept higher US tariffs, and gain markets from global trade diversion around the US. Finally, because of indirect effects, widespread tariffs fail to benefit the protected sectors—a fallacy of composition in a protectionist trade policy.     

Constructing ‘disability’ in Myanmar: teachers,community stakeholders,and the complexity of disability models

This article explores Myanmar teachers’ and community stakeholders’ constructions of disability. We examine how various religious perspectives – particularly Buddhism – inform and shape understandings of impairment and how these beliefs intersect with a strongly medicalised construction of disability. However, in our discussion and exploration of the responses, we also found that the notion of two primary disability ‘models’ – namely the medical model and the social model – lack nuance, complexity, and socio-cultural consideration. Through examining teachers’ and community members’ perspectives of disability in Myanmar, we highlight the importance of socio-cultural variance in understanding local constructions of disability.     

Countering Overseas Power in Global Value Chains: Information Asymmetries and Subcontracting in the Plastics Industry

Resource Dependency Theory (RDT) and Global Value Chain (GVC) analysis have been deployed in the strategic and international management literatures to address questions of power in dyadic relationships and global production networks, respectively. This paper integrates the two theoretical approaches in order to expand RDT, using insights from Hirschman's exit/voice model to show the options available to some firms but not others. Using the relationship between buyers and contract manufacturers from GVC analysis, we find a correlation between firm size and choice of strategic action in response to contract manufacturers' dependence on buyers. Large firms follow an acquiescence strategy while small manufacturers follow an avoidance strategy, able to use both exit and voice strategies. Enabled by scale or control over information, both of these approaches successfully reduce uncertainty and provide a source of sustained competitive advantage. Using a study of the production chain in consumer plastics manufacturing in China, we show how dependent firms respond to GVC induced pressure. We find that based on the size of the contract manufacturer, the range of strategic responses to power is constrained by the nature of the dependency in global value chains. This opens important insights into the role that structural characteristics of organizations (like size) play in determining strategic freedom.     

Optimal control strategies for dividend payments and capital injections in compound Markov binomial risk model with penalties for deficits

We consider the compound Markov binomial risk model. The company controls the amount of dividends paid to the shareholders as well as the capital injections in order to maximize the cumulative expected discounted dividends minus the discounted capital injections and the discounted penalties for deficits prior to ruin. We show that the optimal value function is the unique solution of an HJB equation, and the optimal control strategy is a two-barriers strategy given the current state of the Markov chain. We obtain some properties of the optimal strategy and the optimal condition for ruining the company. We offer a high-efficiency algorithm for obtaining the optimal strategy and the optimal value function. In addition, we also discuss the optimal control problem under a restriction of bounded dividend rates. Numerical results are provided to illustrate the algorithm and the impact of the penalties.     

On Modeling Wood Formation Using Parametric and Semiparametric Regressions for Count Data

Understanding how wood develops has become an important problematic of plant sciences. However, studying wood formation requires the acquisition of count data difficult to interpret. Here, the annual wood formation dynamics of a conifer tree species were modeled using generalized linear and additive models (GLM and GAM); GAM for location, scale, and shape (GAMLSS); a discrete semiparametric kernel regression for count data. The performance of models is evaluated using bootstrap methods. GLM was useful to describe the wood formation general pattern but had a lack of fitting, while GAM, GAMLSS, and kernel regression had a higher sensibility to short-term variations.     

Moments of suprema of random variables

The supremum of random variables representing a sequence of rewards is of interest in establishing the existence of optimal stopping rules. Necessary and sufficient conditions are given for existence of moments of sup_n(X_n ? c_n) and sup_n(S_n ? c_n) where X₁, X₂, … are i.i.d. random variables, S_n = X₁ + … + X_n, and c_n = (nL(n))^1/r, 0 < r < 2, L = 1, L = log, and L = log log. Following Cohn (1974), “rates of convergence” results are used in the proof.     

全球价值链嵌入与技术创新——基于生产分解模型的分析

基于增加值和最终产品的生产分解模型,本文对我国制造业前向与后向产业关联下的全球价值链嵌入进行测度,实证分析全球价值链嵌入对技术创新的作用机理,并在此基础上重点探讨了吸收能力与技术差距两个重要情境因素的调节作用,同时,运用双重差分、工具变量法以及GMM动态面板模型进行稳健性检验,以控制潜在的内生性问题。研究发现:①我国制造业通过嵌入全球价值链的国际间知识溢出效应促进技术创新能力的提升;②吸收能力能够强化这一正向影响关系;③技术差距在后向全球价值链嵌入对技术创新的影响关系中呈倒U 型调节作用,而在前向全球价值链嵌入对技术创新的影响关系中呈正向调节作用。本文推动了网络嵌入理论和知识溢出理论从组织网络向全球价值链领域的繁衍,丰富了全球价值链嵌入领域的研究成果,同时为我国制造业企业在参与国际分工过程中利用全球价值链嵌入实现技术创新能力提升提供重要的理论参考。     

On smoothness of Tukey depth contours

The smoothness of Tukey depth contours is a regularity condition often encountered in asymptotic theory, among others. This condition ensures that the Tukey depth fully characterizes the underlying multivariate probability distribution. In this paper we demonstrate that this regularity condition is rarely satisfied. It is shown that even well-behaved probability distributions with symmetrical, smooth and (strictly) quasi-concave densities may have non-smooth Tukey depth contours, and that the smoothness behaviour of depth contours is fairly unpredictable.     

Predictive Inference for Big,Spatial, Non‐Gaussian Data: MODIS Cloud Data and its Change‐of‐Support

Remote sensing of the earth with satellites yields datasets that can be massive in size, nonstationary in space, and non‐Gaussian in distribution. To overcome computational challenges, we use the reduced‐rank spatial random effects (SRE) model in a statistical analysis of cloud‐mask data from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on board NASA's Terra satellite. Parameterisations of cloud processes are the biggest source of uncertainty and sensitivity in different climate models’ future projections of Earth's climate. An accurate quantification of the spatial distribution of clouds, as well as a rigorously estimated pixel‐scale clear‐sky‐probability process, is needed to establish reliable estimates of cloud‐distributional changes and trends caused by climate change. Here we give a hierarchical spatial‐statistical modelling approach for a very large spatial dataset of 2.75 million pixels, corresponding to a granule of MODIS cloud‐mask data, and we use spatial change‐of‐Support relationships to estimate cloud fraction at coarser resolutions. Our model is non‐Gaussian; it postulates a hidden process for the clear‐sky probability that makes use of the SRE model, EM‐estimation, and optimal (empirical Bayes) spatial prediction of the clear‐sky‐probability process. Measures of prediction uncertainty are also given.