Toward a Decolonial Alternative to Development? The Emergence and Shortcomings of Vivir Bien as State Policy in Bolivia in the Era of Globalization

There is an urgent demand for the examination of the critical perceptions of new kinds of ‘development’ which are emerging in the Global South in response to—and often opposed to—the global capitalist political economy. This article discusses the case of contemporary Bolivia in which indigenous political alternatives have emerged as the resistance to economic globalization and the powers of capital accumulation, as well as to the cultural and epistemological commitments of the Western order. Through an ethnographic approach, it examines the emergence and shortcomings of the notion of vivir bien—a local, decolonial, indigenous concept of good life—as state policy. It argues that despite its transformative potential, the translation of vivir bien discourses into state practices has not been, to a large degree, achieved.     

Changing Partners: Toward a Macrostructural‐Opportunity Theory of Marital Dissolution

We merge marital history data for respondents in the National Survey of Families and Households with census data describing the sex composition of their local marriage markets and occupations to examine the impact of the availability of spousal alternatives on marital dissolution. Proportional hazards regression models that adjust for left truncation reveal that the risk of divorce is highest in geographically defined marriage markets where either husbands or wives encounter numerous alternatives to their current partner. Couples are also more likely to divorce when the wife works in an occupation having relatively many men and few women, but husbands' occupational sex ratio has no effect on the risk of marital dissolution. The destabilizing effects of the availability of spousal alternatives in the local marriage market and in wives' occupations are equally strong among couples with many and few other risk factors for divorce. Our findings suggest that spouses' structural opportunities to form alternative opposite‐sex relationships are an important factor in explaining why some couples divorce.     

Self‐Selective Social Choice Functions Verify Arrow and Gibbard‐Satterthwaite Theorems

This paper introduces a new notion of consistency for social choice functions, called self‐selectivity, which requires that a social choice function employed by a society to make a choice from a given alternative set it faces should choose itself from among other rival such functions when it is employed by the society to make this latter choice as well. A unanimous neutral social choice function turns out to be universally self‐selective if and only if it is Paretian and satisfies independence of irrelevant alternatives. The neutralunanimous social choice functions whose domains consist of linear order profiles on nonempty sets of any finite cardinality induce a class of social welfare functions that inherit Paretianism and independence of irrelevant alternatives in case the social choice function with which one starts is universally self‐selective. Thus, a unanimous and neutral social choice function is universally self‐selective if and only if it is dictatorial. Moreover, universal self‐selectivity for such functions is equivalent to the conjunction of strategy‐proofness and independence of irrelevant alternatives or the conjunction of monotonicity and independence of irrelevant alternatives again.     

Optimality of Equal vs. Unequal Cluster Sizes in Multilevel Intervention Studies: A Monte Carlo Study for Small Sample Sizes

Optimality of equal versus unequal cluster sizes in the context of multilevel intervention studies is examined. A Monte Carlo study is done to examine to what degree asymptotic results on the optimality hold for realistic sample sizes and for different estimation methods. The relative D-criterion, comparing equal versus unequal cluster sizes, almost always exceeded 85%, implying that loss of information due to unequal cluster sizes can be compensated for by increasing the number of clusters by 18%. The simulation results are in line with asymptotic results, showing that, for realistic sample sizes and various estimation methods, the asymptotic results can be used in planning multilevel intervention studies.     

Robust Testing Procedures in Heteroscedastic Linear Models

There exist many studies which treat the robust tests in homoscedastic linear models. However, the robust testing procedure in heteroscedastic linear models has not been examined. In this article, three classes of testing procedures for testing subhypothesis in heteroscedastic linear models are developed. These are Wald-type, score-type, and drop-in dispersion tests. The asymptotic distributions of these tests are obtained under the null hypothesis and contiguous alternatives. For a robustness criterion, the maximum asymptotic bias of the level of the test for distributions in a shrinking contamination neighborhood is used and the most-efficient robust test is derived. Finally, the performance of these tests in small sample is studied by Monte Carlo simulation.     

Analytical Characterization of the Information Matrix for Split-Plot Designs

This article provides the analytical characterization of the inverse of the information matrix for second-order SPD. A particular feature of these explicit expressions is that they are functions of the design parameters enabling the development of analytical functions to efficiently compute exact design optimality criteria. The application of these analytical expressions is demonstrated using the generalized variance of the parameter estimates for second-order SPD. An example illustrating the use of these expressions is also presented.     

A test for zero point triserial correlation coefficient and its relationship with tests for homogeneity of means with ordered alternatives

The point triserial correlation coefficient is defined and, under appropriate order restrictions, an exact test that this correlation coefficient equals zero is developed. The power function of that test is derived and partially tabulated. The general problem of testing for homogeneity of means under ordered alternatives is discussed. The available procedures for performing such tests are considered, are seen to provide alternative approaches to the test developed herein, and are compared with that test. An exact test for the equality of dependent point triserial correlation coefficients is described through application of a procedure suggested by Wolfe ‘1976’     

On Tests of Uniformity for Randomly Distributed Arcs on a Circle

Let n points be independently distributed on a circle. Moving in a counter-clockwise direction, place arcs of length a on the circle with the i^th are starting at the i^th point. We describe three simple tests of the hypothesis of uniformity based on vacancy, on number of spacings and on the length of the maximal spacing. The tests do not require knowledge of the random points. The asymptotic power of these tests is investigated, and it is shown that vacancy-based tests perform best of the three.     

Approximating likelihoods for large spatial data sets

Summary.  Likelihood methods are often difficult to use with large, irregularly sited spatial data sets, owing to the computational burden. Even for Gaussian models, exact calculations of the likelihood for n observations require O ( n ³) operations. Since any joint density can be written as a product of conditional densities based on some ordering of the observations, one way to lessen the computations is to condition on only some of the 'past' observations when computing the conditional densities. We show how this approach can be adapted to approximate the restricted likelihood and we demonstrate how an estimating equations approach allows us to judge the efficacy of the resulting approximation. Previous work has suggested conditioning on those past observations that are closest to the observation whose conditional density we are approximating. Through theoretical, numerical and practical examples, we show that there can often be considerable benefit in conditioning on some distant observations as well.     

Bayesian analysis of hypothesis testing problems for general population: A Kullback–Leibler alternative

We consider a hypothesis problem with directional alternatives. We approach the problem from a Bayesian decision theoretic point of view and consider a situation when one side of the alternatives is more important or more probable than the other. We develop a general Bayesian framework by specifying a mixture prior structure and a loss function related to the Kullback–Leibler divergence. This Bayesian decision method is applied to Normal and Poisson populations. Simulations are performed to compare the performance of the proposed method with that of a method based on a classical z-test and a Bayesian method based on the “0–1” loss.