The Quality of the Urban Environment Around Public Housing Buildings in Montréal: An Objective Approach Based on GIS and Multivariate Statistical Analysis

The question of the “insertion” in space of public housing into the surrounding urban environment is not new. It has often been examined from the perspective of the social environment, but more rarely from that of the physical environment and the accessibility of public and private services and facilities. To qualify the immediate urban environment around Montréal’s public housing buildings in its complexity, we are proposing a methodological approach based on the use of several spatial databases in GIS: (1) the Montréal public housing database, (2) individual census data for the Montréal CMA, (3) a satellite image, (4) a land use map, and (5) location data on a series of public and private services and facilities. Use of these spatial data enables us to identify various combinations of advantages and disadvantages within the urban living environment in which Montréal’s public housing buildings have been located, according to three dimensions: the social environment, the physical environment, and the accessibility of services and facilities. Our final results show that only a small proportion of public housing tenants (7%) live in residual spaces, that is, in quite unattractive areas of the city which combine a number of urban disadvantages: a degraded physical environment, a high level of social deprivation, and few or no services and facilities.

From Potent Dead to Potent Places? Reflections on Muslim Saint Shrines in South Asia

This paper analyses the issue of the thaumaturgy of the Muslim saints in South Asia by focusing on the notion of potent place rather than on the exemplary lives of these figures and on their exceptional relations to God. Nevertheless, there is an important contradiction between the ubiquity of the saint, his residence with God and his strict localisation in space. To establish a firm relation with him and obtain his intercession, devotees must visit him precisely where his corpse was buried. Generally, this place was already potent or extra-ordinary before the inhumation of the saint. Does the process of the saint’s institutionalisation through the rites performed on his body transfer the potency of the place onto the saint and the power of the saint to the place? The analysis will draw on fieldwork enquiries conducted at the shrine of the martyr Ghāzī Miyāñ, the oldest (eleventh century) and most popular Muslim heroic figure in Northern India and Nepalese Terai, and at the shrines of two popular Sufi saints of Sindh (Pakistan), Lāl Shahbāz Qalandar and Bodlo Bahār.     

Dynamic changepoint detection in count time series: a particle filter approach

We study Bayesian dynamic models for detecting changepoints in count time series that present structural breaks. As the inferential approach, we develop a parameter learning version of the algorithm proposed by Chopin [Chopin N. Dynamic detection of changepoints in long time series. Annals of the Institute of Statistical Mathematics 2007;59:349–366.], called the Chopin filter with parameter learning, which allows us to estimate the static parameters in the model. In this extension, the static parameters are addressed by using the kernel smoothing approximations proposed by Liu and West [Liu J, West M. Combined parameters and state estimation in simulation-based filtering. In: Doucet A, de Freitas N, Gordon N, editors. Sequential Monte Carlo methods in practice. New York: Springer-Verlag; 2001]. The proposed methodology is then applied to both simulated and real data sets and the time series models include distributions that allow for overdispersion and/or zero inflation. Since our procedure is general, robust and naturally adaptive because the particle filter approach does not require restrictive specifications to ensure its validity and effectiveness, we believe it is a valuable alternative for dealing with the problem of detecting changepoints in count time series. The proposed methodology is also suitable for count time series with no changepoints and for independent count data.     

Educational inequalities in parental care time: Cross-national evidence from Belgium,Denmark, Spain,and the United Kingdom

This study uses time-diary data for dual-earner couples from Belgium, Denmark, Spain, and the United Kingdom to analyze educational inequalities in parental care time in different national contexts. For mothers, education is significantly associated with parenting involvement only in Spain and the United Kingdom. In Spain these differences are largely explained by inequalities in mothers' time and monetary resources, but not in the United Kingdom, where less-educated mothers disproportionally work in short part-time jobs. For fathers, education is associated with parenting time in Denmark, and particularly in Spain, while the wife's resources substantially drive these associations. On weekends, the educational gradient in parental care time applies only to Spain and the United Kingdom, two countries with particularly large inequalities in parents' opportunities to engage in parenting. The study shows country variations in educational inequalities in parenting, suggesting that socioeconomic resources, especially from mothers, shape important variations in parenting involvement.     

Monte Carlo approximation of likelihood function in spatial GLMMs through an empirical Bayes method

In spatial generalized linear mixed models (SGLMMs), statistical inference encounters problems, since random effects in the model imply high-dimensional integrals to calculate the marginal likelihood function. In this article, we temporarily treat parameters as random variables and express the marginal likelihood function as a posterior expectation. Hence, the marginal likelihood function is approximated using the obtained samples from the posterior density of the latent variables and parameters given the data. However, in this setting, misspecification of prior distribution of correlation function parameter and problems associated with convergence of Markov chain Monte Carlo (MCMC) methods could have an unpleasant influence on the likelihood approximation. To avoid these challenges, we utilize an empirical Bayes approach to estimate prior hyperparameters. We also use a computationally efficient hybrid algorithm by combining inverse Bayes formula (IBF) and Gibbs sampler procedures. A simulation study is conducted to assess the performance of our method. Finally, we illustrate the method applying a dataset of standard penetration test of soil in an area in south of Iran.     

Generalized normal ARMA model applied to the areas of economy,hydrology, and public policy

The main purpose of this article is the presentation of a new class of time series models which is the merge output of the generalized normal distribution with ideas from the GARMA model. Symmetrically, tails that may be lighter or heavier than the Gaussian distribution, and Gaussian and Laplace distributions as special cases, are the main advantages of the use of generalized normal distribution. The proposed model is called generalized normal autoregressive moving average (GN-ARMA). We exemplify the application of the proposed model adjusting it to the three time series, which are from the areas of economy, hydrology, and public policy.     

Comprehensive carrying capacity of the urban agglomeration in the Yangtze River Delta,China

Urban agglomeration (UA) is a complex artificial system. Carrying capacity reflects the environmental capability to support human activity. From the perspective of resource supply and demand, the paper selects 12 representative indicators to evaluate the carrying capacity of land, water, transportation and environment. 16 cities of the UA in the Yangtze River Delta, China, are selected as data samples. Time-series global factor analysis is employed to extract the principal factors of the index of 2000 and 2008. The results show that the comprehensive carrying capacity of the UA tends to benign development as a whole except for Shanghai. Carrying capacities of land and water have become the two critical factors to restrict economic and social development. Based on the hierarchical cluster analysis, the values differentiate the UA into significant gradients. The coefficient of variation shows that the spatial differentiation is conspicuous and expanding. The paper also proposes some policies for the government and planners to successfully design and implement the UA.     

Social and spatial networks: Kinship distance and dwelling unit proximity in rural Thailand

We address a long hypothesized relationship between the proximity of individuals’ dwelling units and their kinship association. Better understanding this relationship is important because of its implications for contact and association among members of a society. In this paper, we use a unique dataset from Nang Rong, Thailand which contains dwelling unit locations (GPS) and saturated kinship networks of all individuals living in 51 agricultural villages. After presenting arguments for a relationship between individuals’ dwelling unit locations and their kinship relations as well as the particulars of our case study, we introduce the data and describe our analytic approach. We analyze how kinship – considered as both a system linking collections of individuals in an extended kinship network and as dyadic links between pairs of individuals – patterns the proximity of dwelling units in rural villages. The results show that in general, extended kin live closer to one another than do unrelated individuals. Further, the degree of relatedness between kin correlates with the distance between their dwelling units. Close kin are more likely to co-reside, a fact which drives much of the relationship between kinship relatedness and dwelling unit proximity within villages. There is nevertheless suggestive evidence of a relationship between kinship association and dwelling unit proximity among kin who do not live together.     

Social networks and spatial configuration—How office layouts drive social interaction

This paper analyzes the spatial dimensions of office layouts in diverse knowledge-intensive workplace environments based on the theoretical and methodological propositions of Space Syntax, and brings this together with the analysis of intra-organizational interaction networks. Physical distances between agents are modeled in different ways and used as explanatory variables in exponential random graph modeling. The paper shows that spatial configuration in offices can be considered an important but not sole rationale for tie formation. Furthermore, it is shown that spatial distance measures based on detailed configurational analysis outperform simple Euclidean distance metrics in predicting social ties.     

县域城乡居民消费结构与收入关系分析

 本文利用福建省县域居民消费样本调查数据,基于空间相关性和扩展线性支出系统,对我国县域居民消费结构与收入关系进行实证分析。结果表明：可支配(纯)收入对居民的各类消费具有显著的影响,而且对八类消费的作用强度不同;旨在提高居民收入的收入分配制度改革能够促进消费需求,针对不同边际消费倾向的政策可以更有效地引导居民消费。本文的分析不同于以往对居民消费结构的研究在于：一是直接使用居民生活状况调查的微观数据进行ELES模型的参数估计,改变了仅使用七类收入群体数据的局限;二是在ELES模型中引入空间因素,考虑了因地理相邻对居民消费结构的影响,分析更为客观合理。