Overview
- Together, the authors have over fifty years of experience working with household datasets, and have written over 200 papers, articles, and reports
- Includes chapters on sampling, causality, Bayesian methods, bootstrapping, impact evaluation, duration models, and modeling spatial effects
- Promotes harnessing of data, particularly from household surveys, to improve policy recommendations
Part of the book series: Statistics for Social and Behavioral Sciences (SSBS)
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About this book
The purpose of this book is to introduce, discuss, illustrate, and evaluate the colorful palette of analytical techniques that can be applied to the analysis of household survey data, with an emphasis on the innovations of the past decade or so.
Most of the chapters begin by introducing a methodological or policy problem, to motivate the subsequent discussion of relevant methods. They then summarize the relevant techniques, and draw on examples – many of them from the authors’ own work – and aim to convey a sense of the potential, but also the strengths and weaknesses, of those techniques.
This book is meant for graduate students in statistics, economics, policy analysis, and social sciences, especially, but certainly not exclusively, those interested in the challenges of economic development in the Third World. Additionally, the book will be useful to academics and practitioners who work closely with survey data. This is a book that can serve as a reference work, to be taken down from the shelf and perused from time to time.
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Keywords
Table of contents (14 chapters)
Reviews
Overall, the book is highly accessible and nicely produced. The authors characterise it as ‘a gateway book’, and I think that, for researchers in policy analysis and household survey work who learnt their trade some time ago, this is an apt description: The book provides an excellent introduction to some of the more recent developments. I shall certainly recommend it to colleagues in the public policy domain...It includes traditional staples such as linear regression and sampling, but also more recent and advanced tools such as the use of directed acyclic graphs in modelling causality, Kohonen networks to group data, Bayesian approaches, propensity score matching, and survival models. It also places considerable emphasis on the power of modern graphical methods – with the consequence that the book has some very attractive colour diagrams, such as bubble plots and cartograms, which certainly demonstrate the power of modern tools.
International Statistical Review, 81, 2, Review by David J. Hand
Authors and Affiliations
About the authors
Jonathan Haughton (Ph.D. Harvard 1983) is Professor of Economics at Suffolk University, and Senior Economist at the Beacon Hill Institute for Public Policy, both in Boston. A specialist in the areas of economic development, international trade, and taxation, and a prize-winning teacher, he has lectured, taught, or conducted research in over a score of countries on five continents. His Handbook on Poverty and Inequality (with Shahidur Khandker) was published by the World Bank in 2009, his articles have appeared in over 30 scholarly journals, and he has written numerous book chapters and over a hundred reports.
Bibliographic Information
Book Title: Living Standards Analytics
Book Subtitle: Development through the Lens of Household Survey Data
Authors: Dominique Haughton, Jonathan Haughton
Series Title: Statistics for Social and Behavioral Sciences
DOI: https://doi.org/10.1007/978-1-4614-0385-2
Publisher: Springer New York, NY
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Science+Business Media, LLC 2011
Hardcover ISBN: 978-1-4614-0384-5Published: 30 August 2011
Softcover ISBN: 978-1-4614-3000-1Published: 27 October 2013
eBook ISBN: 978-1-4614-0385-2Published: 18 September 2011
Series ISSN: 2199-7357
Series E-ISSN: 2199-7365
Edition Number: 1
Number of Pages: XXII, 314