A trichotomic segmentation approach for estimating composite indicators

Composite indicators (CIs) are commonly used for benchmarking of countries over the years, summarizing in a single measurement, complex social, economic, environmental etc. concepts by involving several thematically related sub-indicators. When estimating  CIs and for a few specific countries, it is possible to have a strong indication and belief about their performance, prior to obtaining their scores. Based on that, a number of countries are likely to occupy the top-ranking positions; some will remain at the bottom list, while others may range in intermediate places. This initial preference information imposes a trichotomic segmentation that divides the countries under assessment into categories of superior, inferior and of ambiguous future performance. In this paper, we introduce the trichotomic segmentation as initial preference information to estimate the values of the CIs. We build on the popular Benefit of the Doubt (BoD) method with common weights and develop a two-goal linear programming model, that next to the evaluation of the common weights for the sub-indicators, estimates cut-off points for the CI values that distinguish the superior and inferior countries. The proposed model maintains the advantages of the common variable weighting and produces scores that induce better discrimination of the countries, having also a significant correlation with the original CI scores. The proposed methodology is applied to reassess the Digital Economy and the Society Index.

     

Sample Size Calculation for the Therapeutic Equivalence Problem

A method is proposed for the sample size calculation in the case of therapeutic equivalence of two pharmaceuticals, when the decision is based on post-treatment differences and the post-treatment values are dependent on the pretreatment ones. When the correlation coefficient is large (over 0.7), it is shown that sample size calculation (and the corresponding hypothesis test) based on the sample statistic formed by the mean difference of the post–pre differences of each group has smaller variance and hence leads to smaller sample sizes.     

Local power of panel unit root tests allowing for structural breaks

The asymptotic local power of least squares–based fixed-T panel unit root tests allowing for a structural break in their individual effects and/or incidental trends of the AR(1) panel data model is studied. Limiting distributions of these tests are derived under a sequence of local alternatives, and analytic expressions show how their means and variances are functions of the break date and the time dimension of the panel. The considered tests have nontrivial local power in a N^?1/2 neighborhood of unity when the panel data model includes individual intercepts. For panel data models with incidental trends, the power of the tests becomes trivial in this neighborhood. However, this problem does not always appear if the tests allow for serial correlation in the error term and completely vanishes in the presence of cross-section correlation. These results show that fixed-T tests have very different theoretical properties than their large-T counterparts. Monte Carlo experiments demonstrate the usefulness of the asymptotic theory in small samples.     

Generalized fixed‐T panel unit root tests

Panel data unit root tests, which can be applied to data that do not have many time series observations, are based on very restrictive error and deterministic component specification assumptions. In this paper, we develop a new, doubly modified estimator, based on which we propose a panel unit root test that allows for multiple structural breaks, linear and nonlinear trends, heteroscedasticity, serial correlation, and error cross‐section heterogeneity, when the number of time series observations is finite. The test has the additional perk that it is invariant to the initial condition.     

Data-Transformation and Test of Fit for the Generalized Pareto Hypothesis

In this article, we consider Crámer–von Mises type goodness-of-fit statistics for the Generalized Pareto law. The tests involve a certain transformation of the original observations, which, at least in the case of completely specified null distribution, may be viewed as transforming to uniformity and comparing the resulting moments of arbitrary positive order to those of a uniform distribution. The method is shown to be consistent, and the asymptotic null distribution of the test statistic is derived. Simulation results indicate that the proposed test compares well with standard methods based on the empirical distribution function.     

Foreign policy priorities and ethnic return migration policies: group-level variation in Greece and Serbia

ABSTRACT

Why do ethnoculturally defined states pursue favourable policies to integrate some returnees from their historical diasporas while neglecting or excluding others? We study this question by looking at members of two historical diasporas that, in the 1990s, returned to their respective ethnic homelands, Greece and Serbia, but were not treated uniformly by their respective governments. Utilising a wide range of primary sources, we consider evidence for a number of plausible explanations for such policy variation, including the economic profile of an ethnic returnee group, its status in internal ethnic hierarchies, its lobbying power, and dynamics of party politics. We find, instead, that the observed variation is best explained by the role that each particular group played in the ruling elites’ ex ante foreign policy objectives. Elites discouraged the repatriation of co-ethnics from parts of the world they still had claims over, by pursuing unfavourable repatriation policies. Conversely, absent a revisionist claim, states adopted favourable repatriation policies to encourage their repatriation and facilitate their integration upon return. Methodologically, the article illustrates the importance of focused comparisons across dyads of states and particular sub-diaspora groups.     

The microfoundations of diaspora politics: unpacking the state and disaggregating the diaspora

ABSTRACT

Recognising the need to unpack ?the ‘state’ and? ?problematise? the term? ‘diaspora’, in this special issue we examine the various actors within (and beyond) the state that participate in the design and implementation of diaspora policies, as well as the mechanisms through which ???diasporas?? are constructed by governments, political parties, diaspora entrepreneurs, or international organisations?. Ex??tant theories are often hard-pressed to capture the empirical variation and often end up identifying ‘exceptions’. We?? theorise these ‘exceptions’ through three interrelated? conceptual moves: First, ??we focus on? ??underst?udie?d? aspects of the relationships between states as well as organised non-state actors and their citizens or co-ethnics? abroad (??or at home – in cases of return migration).? Second, ??we? ??examine dyads of ?origin states and specific diasporic communities differentiated by time of emigration, place of residence, socio-economic status, migratory status, generation, or skills. T?hird??,? ?we ?consider? migration in its multiple spatial and temporal phases (emigration, immigration, transit, return??)? and ?how the???y?? inter?sect to?? constitute diasporic identities?? and policies. ??These? conceptual moves contribute to comparative research in the field and allow us to identify the mechanisms? connect?ing structural variable??s with ? specific policies by states ?(and other actors?) as well as responses? by the relevant ?diasporic ?communi?ties??.