“Consumer Confidence” Indexes as social indicators

Consumer Confidence Indexes can be sensibly used in economic and social research conducted in theoretical and methodological framework of social indicators research. They are good predictors of other attitudes, such as voting preferences. Voting preferences are determined much more strongly by expectations of changes in economic conditions than by evaluations of present situation. On the other hand, Consumer Sentiment Indexes — irrespective whether they concern future or present times — are correlated more strongly with leading than with coincident indexes of economic cycles. That proves very important role of predictions, expectations and hopes in attitude formation.     

Europe’s Role in China’s Transition to Superpower Status

What can Western powers do today to ease an eventual global power shift resulting from the rise of superpowers such as China? This paper suggests that part of the answer lies in the same power-binding institutions that allowed the US to rise post WWII without threatening its allies. Continuity in the rules of the global system during a great power transition would promote stability by reducing uncertainty, as well as the extent to which material power can be used coercively. I argue that current superpowers, the EU among them, have an interest in ensuring an equitable distribution of the gains from cooperation. While distributional issues are usually treated in normative terms, they take on very real, material meaning in the context of a great power transition. With this in mind, I look at three aspects of the current global institutional framework that would benefit from reform: international trade and aid, institutional design, and institutional proliferation. In all three cases, a more equal distribution of the gains from institutions today increases the odds that those institutional arrangements will remain in the future.     

Who gets to look nice and who gets to play? Effects of child gender on household expenditures

We examine the relationship between a child’s gender and family expenditure using data from the Polish Household Budget Survey. Having a first-born daughter as compared with a first-born son increases the level of household expenditures on child and adult female clothing, and it reduces spending on games, toys and hobbies. This could be a reflection of a pure gender bias on behalf of the parents or a reflection of gender complementarities between parents’ and children’s expenditures. We find no robust evidence on gender differences in educational investment, measured by kindergarten expenditure. The analysed expenditure patterns suggest a so-far unexamined role of gender in child development. Parents in Poland seem to pay more attention to how girls look and favour boys with respect to activities and play, which could have consequences in adult life and contribute to sustaining gender inequalities and stereotypes.     

Asymptotic behaviour of proportions of observations in random regions determined by central order statistics from stationary processes

In this paper, we show that proportions of observations that fall into a random region determined by a given Borel set and a central order statistic converge almost surely, provided that the corresponding population quantile is unique. We also describe three types of possible asymptotic behaviour of these proportions in the case of non-unique population quantile. As an application of our findings we establish limiting properties of numbers of ties with a central order statistics in a discrete sample. Our results are derived not only for independent and identically distributed observations but more generally for strictly stationary and ergodic sequences of random variables.     

Comparison of the effectiveness of forecasts obtained by means of selected probability functions with respect to forecast error distributions

The forecasting of sales in a company is one of the crucial challenges that must be faced. Nowadays, there is a large spectrum of methods that enable making reliable forecasts. However, sometimes the nature of time series excludes many well-known and widely used forecasting methods (e.g., econometric models). Therefore, the authors decided to forecast on the basis of a seasonally adjusted median of selected probability distributions. The obtained forecasts were verified by means of distributions of the Theil U² coefficient and unbiasedness coefficient.     

The middling mobile: finding place in the liquid city

The middling mobile, differentiated by their modest and unsure mobility, are a vast of bulk of people who intend or expect to move on. As they travel, they tread differing intensities of rhythm and social embeddedness felt to be chaotic, constraining, liberating, or comforting. Owing to their aspirations to ‘get out’ of a rhythmic life, or to move somewhere familiar, the middling mobile use movement and rootedness to navigate and manage everyday life in the liquid city. My analysis offers a holistic exposition of a life that flows between mobility/immobility and rhythmic/arrhythmic forms, and the transitions between them.     

Handling precedence constraints in scheduling problems by the sequence pair representation

In this paper, we show that sequence pair (SP) representation, primarily applied to the rectangle packing problems appearing in the VLSI industry, can be a solution representation of precedence constrained scheduling. We present three interpretations of sequence pair, which differ in complexity of schedule evaluation and size of a corresponding solution space. For each interpretation we construct an incremental precedence constrained SP neighborhood evaluation algorithm, computing feasibility of each solution in the insert neighborhood in an amortized constant time per examined solution, and prove the connectivity property of the considered neighborhoods. To compare proposed interpretations of SP, we construct heuristic and metaheuristic algorithms for the multiprocessor job scheduling problem, and verify their efficiency in the numerical experiment.     

On locally optimal invariant unbiased tests for the variance components ratio in mixed linear models

In the paper the problem of testing of two-sided hypotheses for variance components in mixed linear models is considered. When the uniformly most powerful invariant test does not exist (see e.g. Das and Sinha, in Proceedings of the second international Tampere conference in statistics, 1987; Gnot and Michalski, in Statistics 25:213–223, 1994; Michalski and Zmyślony, in Statistics 27:297–310, 1996) then to conduct the optimal statistical inference on model parameters a construction of a test with locally best properties is desirable, cf. Michalski (in Tatra Mountains Mathematical Publications 26:1–21, 2003). The main goal of this article is the construction of the locally best invariant unbiased test for a single variance component (or for a ratio of variance components). The result has been obtained utilizing Andersson’s and Wijsman’s approach connected with a representation of density function of maximal invariant (Andersson, in Ann Stat 10:955–961, 1982; Wijsman, in Proceedings of fifth Berk Symp Math Statist Prob 1:389–400, 1967; Wijsman, in Sankhyā A 48:1–42, 1986; Khuri et al., in Statistical tests for mixed linear models, 1998) and from generalized Neyman–Pearson Lemma (Dantzig and Wald, in Ann Math Stat 22:87–93, 1951; Rao, in Linear statistical inference and its applications, 1973). One selected real example of an unbalanced mixed linear model is given, for which the power functions of the LBIU test and Wald’s test (the F-test in ANOVA model) are computed, and compared with the attainable upper bound of power obtained by using Neyman–Pearson Lemma.     

On the Complexity of Constructing Evolutionary Trees

In this paper we study a few important tree optimization problems with applications to computational biology. These problems ask for trees that are consistent with an as large part of the given data as possible. We show that the maximum homeomorphic agreement subtree problem cannot be approximated within a factor of , where N is the input size, for any 0 in polynomial time unless P = NP, even if all the given trees are of height 2. On the other hand, we present an O(N log N)-time heuristic for the restriction of this problem to instances with O(1) trees of height O(1) yielding solutions within a constant factor of the optimum. We prove that the maximum inferred consensus tree problem is NP-complete, and provide a simple, fast heuristic for it yielding solutions within one third of the optimum. We also present a more specialized polynomial-time heuristic for the maximum inferred local consensus tree problem.