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Living Standards Analytics: Development through the Lens of Household Survey Data (Statistics for Social and Behavioral Sciences) Hardcover – August 28, 2011

ISBN-13: 978-1461403845 ISBN-10: 1461403847 Edition: 2011th

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Product Details

  • Series: Statistics for Social and Behavioral Sciences
  • Hardcover: 314 pages
  • Publisher: Springer; 2011 edition (August 28, 2011)
  • Language: English
  • ISBN-10: 1461403847
  • ISBN-13: 978-1461403845
  • Product Dimensions: 9.2 x 6.2 x 1 inches
  • Shipping Weight: 1.4 pounds (View shipping rates and policies)
  • Average Customer Review: 5.0 out of 5 stars  See all reviews (1 customer review)
  • Amazon Best Sellers Rank: #3,060,438 in Books (See Top 100 in Books)

Editorial Reviews

Review

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

From the Back Cover

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.

Dominique Haughton is Professor of Mathematical Sciences at Bentley University and Affiliated Researcher at Université Toulouse I.

Jonathan Haughton is Professor of Economics at Suffolk University and Senior Economist at the Beacon Hill Institute for Public Policy.


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1 of 1 people found the following review helpful By LOV on December 4, 2011
Format: Hardcover
I'm fortunate to have read this book. Despite the title "Living Standards Analytics," this is actually a much broader analytics/statistics/econometrics text. It provides reviews of almost all analytic methods that are used in analyzing almost any kind of data. The coverage is so ambitious that you can hardly find a book that can match. It includes basic topics like regression, sampling, cluster analysis and more advanced topics such as Bayesian analysis, causality and program evaluation (where both J. Pearl's Directed Acyclic Graph and D. Rubin's Propensity Score Matching are included), multilevel analysis (random effects models), bootstrapping, and spatial statistics. All topics are presented in a highly practical way with actual examples, illustrated data and recommended software. Since each topic can involve multiple textbooks, the purpose of this book isn't to get into the full details of each but rather provide a strong overview with illustrated examples that are mostly related to living standards.

Personally, I think the title is much too modest for such a wonderful text. I'd strongly recommend it to 1) academic researchers who need a strong overview of various advanced analytic methods for research projects or teaching, 2) industry practitioners who can apply the techniques right away in real data, and 3) applied economists and social scientists who would like to apply advanced analytics for living standards or household survey data.
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