![Analysis of Poverty Data by Small Area Estimation (Wiley Series in Survey Methodology) [??????] Pratesi, Monica](https://d3525k1ryd2155.cloudfront.net/f/014/815/9781118815014.IN.0.m.jpg)
Stock photo: cover may vary
Analysis of Poverty Data by Small Area Estimation (Wiley Series in Survey Methodology) [??????] Pratesi, Monica Hardback - 2016
by Author
- New
A$184.73
A$21.68
Delivery to USA
Standard delivery: 7 to 21 days
More delivery options
Standard delivery: 7 to 21 days
Ships from TextbooksFast (Thailand)
Details
- Title Analysis of Poverty Data by Small Area Estimation (Wiley Series in Survey Methodology) [??????] Pratesi, Monica
- Author Author
- Binding Hardback
- Condition New
- Pages 480
- Volumes 1
- Language ENG
- Publisher Wiley
- Publication date 2016
- Features Bibliography, Index, Maps
- Bookseller's Inventory # 1118815017
- ISBN 9781118815014 / 1118815017
- Weight 1.9 lbs (0.86 kg)
- Dimensions 9.7 x 6.7 x 1 in (24.64 x 17.02 x 2.54 cm)
- Category Mathematics
- Library of Congress subjects Poverty - Statistical methods, Poverty - Measurement
- Library of Congress Catalogue Number 2015035284
- Dewey Decimal Code 339.460
- Quantity available 1
About TextbooksFast Thailand
Biblio member since 2020
We have been in e-commerce for 20 years selling books in many venues. We are specialty in medical and engineering books and well as ELT.
Reader reviews for Analysis of Poverty Data by Small Area Estimation (Wiley Series in Survey Methodology) [??????] Pratesi, Monica
Write a review for this book
Important Terms and Guidelines
- Please focus on the book’s content and context. Also, add any personal comments as to how you enjoyed the book. Substantiate your likes and dislikes. You may make comparisons to other books.
- Reviews must be at least 140 characters in length.
- Please do not reveal critical plot elements.
- This is not a help line. Contact customer support if you need help.
Your review must not include:
- Obscenities, discriminatory language, or other insulting language not suitable for public domain
- Advertisements, “spam” content, or references to other products, offers or websites.
- Email addresses, URLs, phone numbers, physical addresses or other contact information.
- Overly critical comments about other reviews or reviewers
- Time-sensitive material (i.e. promotional tours, seminars, lectures, etc.)
- Availability, price, or alternative ordering/shipping information
From the rear cover
A comprehensive guide to implementing SAE methods for poverty studies and poverty mapping
There is an increasingly urgent demand for poverty and living conditions data, in relation to local areas and/or subpopulations. Policy makers and stakeholders need indicators and maps of poverty and living conditions in order to formulate and implement policies, (re)distribute resources, and measure the effect of local policy actions.
Small Area Estimation (SAE) plays a crucial role in producing statistically sound estimates for poverty mapping. This book offers a comprehensive source of information regarding the use of SAE methods adapted to these distinctive features of poverty data derived from surveys and administrative archives. The book covers the definition of poverty indicators, data collection and integration methods, the impact of sampling design, weighting and variance estimation, the issue of SAE modelling and robustness, the spatio-temporal modelling of poverty, and the SAE of the distribution function of income and inequalities. Examples of data analyses and applications are provided, and the book is supported by a website describing scripts written in SAS or R software, which accompany the majority of the presented methods.
Key features
- Presents a comprehensive review of SAE methods for poverty mapping
- Demonstrates the applications of SAE methods using real-life case studies
- Offers guidance on the use of routines and choice of websites from which to download them
Analysis of Poverty Data by Small Area Estimation offers an introduction to advanced techniques from both a practical and a methodological perspective, and will prove an invaluable resource for researchers actively engaged in organizing, managing and conducting studies on poverty.
