Living Standards Analytics

Development through the Lens of Household Survey Data
2011
ISBN: 978-1-4614-0384-5
Verlag: Springer

Buch, Englisch, 314 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 670 g

Reihe: Statistics for Social and Behavioral Sciences

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.

Zielgruppe

Research

Autoren/Hrsg.

Haughton, Jonathan

Haughton, Dominique

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Fuzzy-Systeme
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
• Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein Empirische Sozialforschung, Statistik
• Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Wirtschaftsstatistik, Demographie
• Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein Demographie, Demoskopie
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Mustererkennung, Biometrik
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse

Inhaltsverzeichnis

Introduction.- Graphical exploratory methods.- Sample size issues.- Beyond linear regression.- Adjustment for spatial correlation.- The issue of causality.- Non-homogeneity/mixtures.- Bayesian analysis.- Grouping methods.- Panel data issues.- Measures of poverty and inequality.- Bootstrap.- Fuzzy methods for poverty measures.- Combining data sets.

Über Autor(innen)

Dominique Haughton (Ph.D. MIT 1983) is Professor of Mathematical Sciences at Bentley University in Waltham, Massachusetts, near Boston, and Affiliated Researcher at the Université Toulouse 1, France.  Her major areas of interest are applied statistics, statistics and marketing, the analysis of living standards surveys, data mining, and model selection. She is the editor-in-chief of Case Studies in Business, Industry and Government Statistics (CSBIGS), and has published over fifty articles in scholarly journals, including The American Statistician, Annals of Statistics, Sankhya, Communications in Statistics, and Statistica Sinica. Dominique is a Fellow of the American Statistical Association.

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.