Computational tools for poverty measurement and analysis

This paper introduces some relatively straightforward computational tools for estimating poverty measures from the sort of data that are typically available from published sources. All that is required for using these tools is an elementary regression package. The methodology also easily lends itself to a number of poverty simulations, some of which are discussed. The paper addresses the central question: How do we construct poverty measures from grouped data on consumption and income? Two broad approaches can be identified: simple interpolation methods and methods based on parameterized Lorenz curves. The paper briefly describes the two approaches and discusses why the second may be considered preferable.Income. ,Consumption (Economic theory) ,Poverty Research Methodology. ,

Poverty in India and Indian states

A complete and updated series on poverty measures for India is presented spanning the period 1951–1994. The series are presented at the all-India level as well as for 15 major states, and for rural and urban sectors separately. Key features of the evolution of poverty in India are described.Poverty India ,

Soft Seeded SSL Graphs for Unsupervised Semantic Similarity-based Retrieval

Semantic similarity based retrieval is playing an increasingly important role in many IR systems such as modern web search, question-answering, similar document retrieval etc. Improvements in retrieval of semantically similar content are very significant to applications like Quora, Stack Overflow, Siri etc. We propose a novel unsupervised model for semantic similarity based content retrieval, where we construct semantic flow graphs for each query, and introduce the concept of "soft seeding" in graph based semi-supervised learning (SSL) to convert this into an unsupervised model. We demonstrate the effectiveness of our model on an equivalent question retrieval problem on the Stack Exchange QA dataset, where our unsupervised approach significantly outperforms the state-of-the-art unsupervised models, and produces comparable results to the best supervised models. Our research provides a method to tackle semantic similarity based retrieval without any training data, and allows seamless extension to different domain QA communities, as well as to other semantic equivalence tasks.Comment: Published in Proceedings of the 2017 ACM Conference on Information and Knowledge Management (CIKM '17

Determinants of Poverty in Egypt

Poverty alleviation Egypt ,Development policies ,Food prices Government policy Egypt ,Agricultural wages ,