Variational Bayes model averaging for graphon functions and motif frequencies inference in W-graph models

W-graph refers to a general class of random graph models that can be seen as a random graph limit. It is characterized by both its graphon function and its motif frequencies. In this paper, relying on an existing variational Bayes algorithm for the stochastic block models along with the corresponding weights for model averaging, we derive an estimate of the graphon function as an average of stochastic block models with increasing number of blocks. In the same framework, we derive the variational posterior frequency of any motif. A simulation study and an illustration on a social network complete our work

Estimating propensity scores with missing covariate data using general location mixture models

In many observational studies, researchers estimate causal effects using propensity scores, e.g., by matching or sub-classifying on the scores. Estimation of propensity scores is complicated when some values of the covariates aremissing. We propose to use multiple imputation to create completed datasets, from which propensity scores can be estimated, with a general location mixture model. The model assumes that the control units are a latent mixture of (i)units whose covariates are drawn from the same distributions as the treated units’ covariates and (ii) units whose covariates are drawn from different distributions. This formulation reduces the influence of control units outside the treated units’ region of the covariate space on the estimation of parameters in the imputation model, which can result in more plausible imputations and better balance in the true covariate distributions. We illustrate the benefits of 1 the latent class modeling approach with simulations and with an observationalstudy of the effect of breast feeding on children’s cognitive abilities

Estimating propensity scores with missing covariate data using general location mixture models

In many observational studies, researchers estimate causal effects using propensity scores, e.g., by matching or sub-classifying on the scores. Estimation of propensity scores is complicated when some values of the covariates aremissing. We propose to use multiple imputation to create completed datasets, from which propensity scores can be estimated, with a general location mixture model. The model assumes that the control units are a latent mixture of (i)units whose covariates are drawn from the same distributions as the treated units’ covariates and (ii) units whose covariates are drawn from different distributions. This formulation reduces the influence of control units outside the treated units’ region of the covariate space on the estimation of parameters in the imputation model, which can result in more plausible imputations and better balance in the true covariate distributions. We illustrate the benefits of 1 the latent class modeling approach with simulations and with an observationalstudy of the effect of breast feeding on children’s cognitive abilities

The Geographical Patterns of Socio-Economic Well-Being of First Nations Communities in Canada

Community/Rural/Urban Development, Labor and Human Capital,

College Students\u27 Attitudes on Neighborhood Integration: From the Classroom to the Community and Back Again

I grew up in an all white suburb, well, almost all white. There were two black families that literally lived on the wrong side of the tracks. Two large run-down old houses sat within five feet of the rumbling trains. Sometimes my family drove past those houses in our old station wagon. On days that our drive was interrupted by a crossing train, I would watch the barefoot black children playing by the street. I never thought of our suburb as being segregated, at least not until I was in high school

DEVELOPMENT AND POVERTY REDUCTION: DO INSTITUTIONS MATTER? A STUDY ON THE IMPACT OF LOCAL INSTITUTIONS IN RURAL INDIA

The paper examines the impact of local institutions on development and poverty in the rural areas of India. Recent research on the role of institutions on the path of economic development indicates the importance of both "macro" and "micro" institutions including local institutions. The study finds a large number of both formal and informal local institutions in the surveyed villages, and a substantial degree of interaction of the households with the institutions. These include both formal institutions such as service cooperatives and dairy cooperatives, as well as informal institutions such as savings groups, community associations and labour groups. The study finds that apart from the standard factors included such as land, capital and labour, the presence and membership in local institutions plays a significant role in explaining the variation in household incomes and gain in capital assets over time. Savings/ micro-credit groups, and dairy cooperatives are found to be particularly important. Further, membership in these institutions is not found to be related to high asset levels or high caste - it is often inversely so. This indicates a stronger developmental role. Recorded opinions of the households supports the findings on the impact and beneficial role of local institutions. The study confirms that institutions do matter, and that local institutions can and do make a significant contribution in helping development in the rural areas, especially so for the lower income groups.Institutions, development, poverty reduction, International Development,

03-08 "International Trade and Air Pollution: The Economic Costs of Air Emissions from Waterborne Commerce Vessels in the United States"

Although there is a burgeoning literature on the effects of international trade on the environment, relatively little work has been done on where trade most directly effects the environment: the transportation sector. This article shows how international trade is affecting criteria air pollution emissions in the United States’ shipping sector. Recent work has shown that cargo ships have been long overlooked regarding their contribution to air pollution. Indeed, ship emissions have recently been deemed “the last unregulated source of traditional air pollutants.” Air pollution from ships has a number of significant local, national, and global environmental effects. Building on past studies, we examine the economic costs of this increasing and unregulated form of environmental damage. We find that total emissions from ships are largely increasing due to the increase in foreign commerce (or international trade):

Permanents, Pfaffian orientations, and even directed circuits

Given a 0-1 square matrix A, when can some of the 1's be changed to -1's in such a way that the permanent of A equals the determinant of the modified matrix? When does a real square matrix have the property that every real matrix with the same sign pattern (that is, the corresponding entries either have the same sign or are both zero) is nonsingular? When is a hypergraph with n vertices and n hyperedges minimally nonbipartite? When does a bipartite graph have a "Pfaffian orientation"? Given a digraph, does it have no directed circuit of even length? Given a digraph, does it have a subdivision with no even directed circuit? It is known that all of the above problems are equivalent. We prove a structural characterization of the feasible instances, which implies a polynomial-time algorithm to solve all of the above problems. The structural characterization says, roughly speaking, that a bipartite graph has a Pfaffian orientation if and only if it can be obtained by piecing together (in a specified way) planar bipartite graphs and one sporadic nonplanar bipartite graph.Comment: 47 pages, published versio