Forum 4: the environmental privilege of borders in the anthropocene

ABSTRACT

Mobility can indicate a powerful or privileged relationship with one’s environment. The ability to exercise mobility or not (of oneself or others) is an exertion of power that demarcates where particular people belong and under what kind of environmental conditions. This essay focuses on the significance of borders in creating environmental privilege in the Anthropocene. Environmental privilege is accrued through the exercise of economic, political, and cultural power that enables the construction of exclusive environmental amenities such as clean air and water, open space, and safe neighborhoods. For years, environmental justice scholars have revealed the burdens and oppressive conditions associated with environmental inequality, but few studies consider the flipside of that reality. We argue that environmental privileges enjoyed by some rest upon the manipulation of the mobility of others – human and nonhuman. We believe border making will come under greater pressure as the effects of climate change increase, and the volume of resources required to maintain exclusive spaces intensifies. Continued mass migration will bring heightened anxieties about national identity and calls for greater border enforcement, despite the reality that borders – both literal and figurative – consistently fail to alleviate migratory pressures while exacerbating the effects of climate change and environmental injustice. Our research shows that greater ecological instability increases efforts to create privatized places as pristine spaces untouched by global turmoil, thereby reinforcing those social forces that produce environmental injustices in the first place.     

An exploratory study on the potential of social enterprise to act as the institutional glue of network governance

This study combines two topics of contemporary salience for public administration: social enterprise and governance networks. While operating at different levels, both are institutions which attempt to draw together the three pillars of state, market, and civil society. Nevertheless, the respective literatures focus on particular aspects of the three pillars. We connect the two concepts and suggest that some social enterprises can act as the institutional glue of networks due to their ability to benefit organizations in each of the three sectors. This requires social enterprises to have the managerial capacity to diffuse social know-how, and is facilitated by the trust of other organizations and a supportive policy framework. The links are explicated at the conceptual level before providing evidence from South Korea and the UK. Finally, research propositions are offered, which suggest new avenues for future research.     

Multivariate regression models for discrete and continuous repeated measurements

A general class of multivariate regression models is considered for repeated measurements with discrete and continuous outcome variables. The proposed model is based on the seemingly unrelated regression model (Zellner, 1962) and an extension of the model of Park and Woolson(1992). The regression parameters of the model are consistently estimated using the two-stage least squares method. When the out come variables are multivariate normal, the two-stage estimator reduces to Zellner’s two-stage estimator. As a special case, we consider the marginal distribution described by Liang and Zeger (1986). Under this this distributional assumption, we show that the two-stage estimator has similar asymptotic properties and comparable small sample properties to Liang and Zeger's estimator. Since the proposed approach is based on the least squares method, however, any distributional assumption is not required for variables outcome variables. As a result, the proposed estimator is more robust to the marginal distribution of outcomes.     

Distances between normal populations when covariance matrices are unequal

The definition of distance between two populations of equal covariance matrices is extended to two and more than two populations with unequal covariance matrices and Rao’s U test for testing the conditional contribution of a subset of variables to the distance is extended to this situation, even when sample sizes are not necessarily the same.     

Some remarks on the chi-squared test with both margins fixed

Under the hypothesis of independence, the chi-squared test statistic for independence in a two-way contingency table follows an asymptotic chi-squared distribution under both a multinomial and a product-multinomial models. Alalouf(1987) showed the same result holds for the third case where both margins are fixed. In this paper an intuitively easier way of proof using the conditional limit theorems is suggested and some points are discussed.     

On the sums of probability functions of order statistics

When a random vector is independent and identically distributed, we have expressed the sums of the marginal probability functions of the order statistics of the random vector in terms of the common marginal probability functions of the random vector. We have also derived the relationships between the sums of the joint probability functions of two order statistics of the random vector and the common marginal probability functions of the random vector.     

Simplified Maximum Likelihood Inference Based on the Likelihood Decomposition for Missing Data

In this paper, we propose an estimation method when sample data are incomplete. We decompose the likelihood according to missing patterns and combine the estimators based on each likelihood weighting by the Fisher information ratio. This approach provides a simple way of estimating parameters, especially for non‐monotone missing data. Numerical examples are presented to illustrate this method.     

Central Limit Theorems for Reduced U‐Statistics Under Dependence and Their Usefulness

A reduced ‐statistic is a ‐statistic with its summands drawn from a restricted but balanced set of pairs. In this article, central limit theorems are derived for reduced ‐statistics under ‐mixing, which significantly extends the work of Brown & Kildea in various aspects. It will be shown and illustrated that reduced ‐statistics are quite useful in deriving test statistics in various nonparametric testing problems.     

Robust minimum distance inference based on combined distances

The minimum disparity estimators proposed by Lindsay (1994) for discrete models form an attractive subclass of minimum distance estimators which achieve their robustness without sacrificing first order efficiency at the model. Similarly, disparity test statistics are useful robust alternatives to the likelihood ratio test for testing of hypotheses in parametric models; they are asymptotically equivalent to the likelihood ratio test statistics under the null hypothesis and contiguous alternatives. Despite their asymptotic optimality properties, the small sample performance of many of the minimum disparity estimators and disparity tests can be considerably worse compared to the maximum likelihood estimator and the likelihood ratio test respectively. In this paper we focus on the class of blended weight Hellinger distances, a general subfamily of disparities, and study the effects of combining two different distances within this class to generate the family of “combined” blended weight Hellinger distances, and identify the members of this family which generally perform well. More generally, we investigate the class of "combined and penal-ized" blended weight Hellinger distances; the penalty is based on reweighting the empty cells, following Harris and Basu (1994). It is shown that some members of the combined and penalized family have rather attractive properties