The Modeling and Seasonal Adjustment of Weekly Observations

Several important economic time series are recorded on a particular day every week. Seasonal adjustment of such series is difficult because the number of weeks varies between 52 and 53 and the position of the recording day changes from year to year. In addition certain festivals, most notably Easter, take place at different times according to the year. This article presents a solution to problems of this kind by setting up a structural time series model that allows the seasonal pattern to evolve over time and enables trend extraction and seasonal adjustment to be carried out by means of state-space filtering and smoothing algorithms. The method is illustrated with a Bank of England series on the money supply.     

Developing an Index to Measure Sub-municipal Level Urban Sprawl

The present study aims to develop an index composed of different spatial variables to measure the urban sprawl levels of a municipality located in Southern Spain. According to the findings, urban sprawl can be measured not only on the metropolitan level but also on a more detailed and precise level, such as sub-municipal. A group of experts chosen for their suitability in measuring urban sprawl select six spatial variables (population density, net residential density, coverage ratio, land use types, percentage of residential land use, and average year of construction). These variables are aggregated using Choquet integral, a technique that combines interactions between those variables providing greater coherence to the complexity that is inherent in the creation of composite sprawl indexes. This methodology has been demonstrated to be valid and appropriate in evaluating urban expansion at sub-municipal level, but can also be applied to other scales once it is clearly a phenomenon in which interaction between criteria exists. The resulting composite index allows the assignment of different levels of sprawl to the urban areas consistent with their morphology and landscape.     

Measuring Multidimensional Poverty According to National Definitions: Operationalising Target 1.2 of the Sustainable Development Goals

Social Indicators Research - The first Sustainable Development Goal (SDG) tasks countries with eradicating poverty in all its dimensions according to national definitions. This presents...     

Model-based clustering with determinant-and-shape constraint

Statistics and Computing - Model-based approaches to cluster analysis and mixture modeling often involve maximizing classification and mixture likelihoods. Without appropriate constrains on the...     

Who’s About to Leave? A Global Survey of Aspirations and Intentions to Migrate

This article analyses aspirations and intentions to migrate based on Gallup World Poll for the period 2010–2015. We estimate individual‐level traits associated with aspirations and intentions to migrate across groups of countries in different regions and with different income levels. This paper brings together previous hypotheses regarding migration aspirations and tests them under several specifications, while keeping separate findings according to migration aspirations and intentions to appreciate differences between them. Being dissatisfied with one’s own standard of living is associated with a higher probability of desiring to move, while the relation with the actual preparation to migrate is less clear. Some individual traits remain significant across (almost) all specifications: being male, foreign‐born, highly educated, and having networks abroad are associated with higher probability of preparing for international migration. Aspects related to one’s economic situation are not consistently significant across specifications, signalling the importance of contextual analyses for these factors.     

Applying the Consensual Method of Estimating Poverty in a Low Income African Setting

Social Indicators Research - We present the first study of multidimensional poverty in Benin using the consensual or socially perceived necessities approach. There is a remarkable level consensus...     

Interpersonal Distances in Group Walking

The spatial organization of 1,020 groups comprised of adolescents and young adults, observed in an ecological setting while walking, was analyzed. Observations were made in an urban environment where walking speed could be considered. The results showed that male dyads and triads tended to walk abreast less often than female dyads. Mixed dyads walked abreast more often than same-sex dyads; and the males preceded the females in two-thirds of the cases. The male groups walked at a higher rate of speed than the female groups. Walking speed was correlated to misalignment between group members when walking. The most frequent spatial arrangement in triads was a “<” formation (as seen from above, while the walking direction was from left to right), with the middle individual positioned slightly behind in comparison to the lateral individuals. Groups comprised of more than three individuals tended to split themselves into single individuals, dyads, and triads.     

Internal slackening scoring methods

We deal with the ranking problem of the nodes in a directed graph. The bilateral relationships specified by a directed graph may reflect the outcomes of a sport competition, the mutual reference structure between websites, or a group preference structure over alternatives. We introduce a class of scoring methods for directed graphs, indexed by a single nonnegative parameter α. This parameter reflects the internal slackening of a node within an underlying iterative process. The class of so-called internal slackening scoring methods, denoted by λ ^α , consists of the limits of these processes. It is seen that λ⁰ extends the invariant scoring method, while λ ^∞ extends the fair bets scoring method. Method λ¹ corresponds with the existing λ-scoring method of Borm et al. (Ann Oper Res 109(1):61–75, 2002) and can be seen as a compromise between λ⁰ and λ ^∞ . In particular, an explicit proportionality relation between λ ^α and λ¹ is derived. Moreover, the internal slackening scoring methods are applied to the setting of social choice situations where they give rise to a class of social choice correspondences that refine both the Top cycle correspondence and the Uncovered set correspondence.     

Some results for maximum likelihood estimation of adjusted relative risks

Maximum likelihood (ML) estimation of relative risks via log-binomial regression requires a restricted parameter space. Computation via non linear programming is simple to implement and has high convergence rate. We show that the optimization problem is well posed (convex domain and convex objective) and provide a variance formula along with a methodology for obtaining standard errors and prediction intervals which account for estimates on the boundary of the parameter space. We performed simulations under several scenarios already used in the literature in order to assess the performance of ML and of two other common estimation methods.