This volume explores the analytical techniques involved with household survey data analysis. Policy problems motivate a discussion of relevant methods, while examples from the author's own work illustrate the strengths and weaknesses of the techniques discussed.

The purpose of this book is to compile, discuss, illustrate and evaluate the wide range of analytical techniques that can be applied to the analysis of household survey data, with emphasis on the innovations of the past decade.

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

Autorentext
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.

Inhalt
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.