Similarity-Based Classification in Partially Labeled Networks

We propose a similarity-based method, using the similarity between nodes, to address the problem of classification in partially labeled networks. The basic assumption is that two nodes are more likely to be categorized into the same class if they are more similar. In this paper, we introduce ten similarity indices, including five local ones and five global ones. Empirical results on the co-purchase network of political books show that the similarity-based method can give high accurate classification even when the labeled nodes are sparse which is one of the difficulties in classification. Furthermore, we find that when the target network has many labeled nodes, the local indices can perform as good as those global indices do, while when the data is sparce the global indices perform better. Besides, the similarity-based method can to some extent overcome the unconsistency problem which is another difficulty in classification.Comment: 13 pages,3 figures,1 tabl

From random walks to distances on unweighted graphs

Large unweighted directed graphs are commonly used to capture relations between entities. A fundamental problem in the analysis of such networks is to properly define the similarity or dissimilarity between any two vertices. Despite the significance of this problem, statistical characterization of the proposed metrics has been limited. We introduce and develop a class of techniques for analyzing random walks on graphs using stochastic calculus. Using these techniques we generalize results on the degeneracy of hitting times and analyze a metric based on the Laplace transformed hitting time (LTHT). The metric serves as a natural, provably well-behaved alternative to the expected hitting time. We establish a general correspondence between hitting times of the Brownian motion and analogous hitting times on the graph. We show that the LTHT is consistent with respect to the underlying metric of a geometric graph, preserves clustering tendency, and remains robust against random addition of non-geometric edges. Tests on simulated and real-world data show that the LTHT matches theoretical predictions and outperforms alternatives.Comment: To appear in NIPS 201

Public Policies versus Institutional Structures: A New Perspective of Assessing Economic Growth Dynamics in Developing Nations

This study is performed to find out the impact of policy and institutional factors on the economic growth of the developing countries. These include Economic management, Structural policies, Social inclusion/equity and Governance. Panel data of 72 countries is being taken for this study and the time period is from 2005-2013. Simple ordinary least square (OLS) model has been applied to find the impact of these variables on economic growth of developing countries and the results showed that overall institutions are related more to the economic growth of these nations as compared to policy contents. On the other side from institutional parameters, role of budgetary management and equity of public resource use by the government is positively contributing to economic performance of these nations. Nevertheless few variables have showed negative impact as well in which the process resource mobilization and transparency of the system is exhibiting more negative role in economic growth of these nations. Overall results showed that non-economic parameters of the political systems are more closely interrelated with the process of economic growth in these nation as compared to pure economic factors. Key Words: Fiscal Policy, Economic Integration, Budget, Debt Management, Government Regulations, Economic Development JEL Classification: E63, F15, H61, H63, I18, O1

FRAGILITY AND MDG PROGRESS: HOW USEFUL IS THE FRAGILITY CONCEPT?

While progress in developing countries as a whole, in terms of growth, poverty reduc-tion, and several MDGs, has been quite good in recent years, fragile states lag behind in levels of MDG achievement. To understand the link between fragility and MDG progress, and also to identify the most effective policy interventions to achieve the MDGs, it is es-sential that fragile states are appropriately defined and classified. While the amount of literature on how to engage with fragile states is rapidly accumulating, only very limited analysis exists that investigates to what extent the levels and trends in the MDGs differ significantly between different definitions of fragile and non-fragile states. The purpose of this paper is to investigate the usefulness of the fragile state concept in tracking the levels and progress of the MDGs. In doing so, this paper applies several definitions of fragility in order to study the MDG progress between 1990 and 2006. It compares aver-age performance in levels and trends of MDG progress between fragile and non-fragile countries and also compares within-group heterogeneity. The paper shows that fragile countries are, indeed, performing worse in terms of MDG levels. In terms of MDG pro-gress, progress is not necessarily slower in fragile states. Only a rather small number of countries suffering from compound disadvantages are doing significantly worse in terms of MDG progress. Lastly, the heterogeneity of MDG performance among fragile states is so large that it is not very useful to treat them as a group; the problems they face, as well as the solutions required, differ greatly and have to be developed and treated sui generis.Fragile States, Millennium Development Goals, Heterogeneity.