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In 2013, the World Bank Group announced two goals that would guide its operations worldwide. First is the eradication of chronic extreme poverty bringing the number of extremely poor people, defined as those living on less than 1.25 purchasing power parity (PPP)†“adjusted dollars a day, to less than 3 percent of the world’s population by 2030.The second is the boosting of shared prosperity, defined as promoting the growth of per capita real income of the poorest 40 percent of the population in each country. In 2015, United Nations member nations agreed in New York to a set of post-2015 Sustainable Development Goals (SDGs), the first and foremost of which is the eradication of extreme poverty everywhere, in all its forms. Both the language and the spirit of the SDG objective reflect the growing acceptance of the idea that poverty is a multidimensional concept that reflects multiple deprivations in various aspects of well-being. That said, there is much less agreement on the best ways in which those deprivations should be measured, and on whether or how information on them should be aggregated. Monitoring Global Poverty: Report of the Commission on Global Poverty advises the World Bank on the measurement and monitoring of global poverty in two areas: What should be the interpretation of the definition of extreme poverty, set in 2015 in PPP-adjusted dollars a day per person? What choices should the Bank make regarding complementary monetary and nonmonetary poverty measures to be tracked and made available to policy makers? The World Bank plays an important role in shaping the global debate on combating poverty, and the indicators and data that the Bank collates and makes available shape opinion and actual policies in client countries, and, to a certain extent, in all countries. How we answer the above questions can therefore have a major influence on the global economy.
Poverty is a paradoxical state. Recognizable in the eld for any sensitive observer who travels in remote rural areas and urban slums and meets marginalized people in a given society, poverty still remains a challenge to conceptual formalization and to measurement that is consistent with such formalization. The analysis of poverty is multidisciplinary. It goes from ethics to economics, from political science to human biology, and any type of measurement rests on mathematics. Moreover, poverty is multifaceted according to the types of deprivation, and it is also gender and age speci c. A vector of variables is required, which raises a substantial problem for individual and group comparisons necessary to equity analysis. Multidimension- ity also complicates the aggregation necessary to perform the ef ciency analysis of policies. In the case of income poverty, these two problems, equity and ef ciency, have bene ted from very signi cant progress in the eld of economics. Similar achievements are still to come in the area of multidimensional poverty. Within this general background, this book has a very modest and narrow-scoped objective. It proposes an operational methodology for measuring multidimensional poverty, independent from the conceptual origin, the size and the qualitative as well as the quantitative nature of the primary indicators used to describe the poverty of an individual, a household or a sociodemographic entity.
The aim of this book is to explore the challenges facing rural communities and economies and to demonstrate the potential of spatial microsimulation for policy and analysis in a rural context. This is done by providing a comprehensive overview of a particular spatial microsimulation model called SMILE (Simulation Model of the Irish Local Economy). The model has been developed over a ten year period for applied policy analyis in Ireland which is seen as an ideal study area given its large percentage of population living in rural areas. The book reviews the policy context and the state of the art in spatial microsimulation against which SMILE was developed, describes in detail its model design and calibration, and presents example of outputs showing what new information the model provides using a spatial matching process. The second part of the book explores a series of rural issues or problems, including the impacts of new or changing government or EU policies, and examines the contribution that spatial microsimulation can provide in each area.
This book is a practical guide on how to design, create and validate a spatial microsimulation model. These models are becoming more popular as academics and policy makers recognise the value of place in research and policy making. Recent spatial microsimulation models have been used to analyse health and social disadvantage for small areas; and to look at the effect of policy change for small areas. This provides a powerful analysis tool for researchers and policy makers. This book covers preparing the data for spatial microsimulation; a number of methods for both static and dynamic spatial microsimulation models; validation of the models to ensure the outputs are reasonable; and the future of spatial microsimulation. The book will be an essential handbook for any researcher or policy maker looking to design and create a spatial microsimulation model. This book will also be useful to those policy makers who are commissioning a spatial microsimulation model, or looking to commission work using a spatial microsimulation model, as it provides information on the different methods in a non-technical way.