You are here

Disable VAT on Taiwan

Unfortunately, as of 1 January 2020 SAGE Ltd is no longer able to support sales of electronically supplied services to Taiwan customers that are not Taiwan VAT registered. We apologise for any inconvenience. For more information or to place a print-only order, please contact uk.customerservices@sagepub.co.uk.

Methods for Quantitative Macro-Comparative Research
Share
Share

Methods for Quantitative Macro-Comparative Research



August 2013 | 296 pages | SAGE Publications, Inc

Will a one-child policy increase economic growth?  Does globalization contribute to global warming?  Are unequal societies less healthy than more egalitarian societies? 

It is questions like these that social scientists turn to quantitative macro-comparative research (QMCR) to answer. Although many social scientists understand statistics conceptually, they struggle with the mathematical skills required to conduct QMCR. This non-mathematical book is intended to bridge that gap, interpreting the advanced statistics used in QMCR in terms of verbal descriptions that any college graduate with a basic background in statistics can follow. It addresses both the philosophical foundations and day-to-day practice of QMCR in an effort to improve research outcomes and ensure policy relevance.

A comprehensive guide to QMCR, the book presents an overview of the questions that can be answered using QMCR, details the steps of the research process, and concludes with important guidelines and best practices for conducting QMCR. The book assumes that the reader has a sound grasp of the fundamentals of linear regression modeling, but no advanced mathematical knowledge is required in order for researchers and students to read, understand, and enjoy the book. A conversational discussion style supplemented by 75 tables and figures makes the book's methodological arguments accessible to both students and professionals. Extensive citations refer readers back to primary discussions in the literature, and a comprehensive index provides easy access to coverage of specific techniques.


 
PART I: MACRO-COMPARATIVE DATA STRUCTURES
 
1. The Logic of Macro-Comparative Research
 
2. The International Data Infrastructure
 
3. Variable Operationalization
 
4. The Structure of Country Data
 
PART II: STATISTICAL ANALYSIS OF MACRO-COMPARATIVE DATA
 
5. Statistical Modeling with Cross-Sectional Designs
 
6. Structured and Longitudinal Designs for Establishing Causality
 
7. Repeated Measures and Multilevel Modeling
 
8. An Interpretive Research and Policy Framework
 
Conclusion: The Political Economy of Quantitative Macro-Comparative Research

 “There isn’t any text I am aware of like this, and as the author notes, there is an increasing amount of interest in this area, so a text is needed.”

Richard York, University of Oregon 

Richard York
University of Oregon
Richard York

“All too often statistical analysis texts lose sight of the reasons for conducting the research in the first place, but that is certainly not the case here…The chapters thus far actually go far beyond much of the current work by both synthesizing a wide variety of material and explicitly dealing with many of the taken for granted assumptions…All of the writing is quite clear, even when it verges into quite complex methodological territory.  The examples are well chosen.”

Buster Smith, Catawba College 

Buster Smith
Catawba College
Buster Smith

“This should be required reading for World Bank, OECD and U.N. researchers and data collectors as well as applied and academic sociologists, economists, political scientists and others who conduct cross country comparisons using publicly available large datasets.

Ernesto Castañeda, University of Texas at El Paso 

Ernesto Castañeda
University of Texas at El Paso
Ernesto Castañeda

“I really don’t know how the author has managed it, but he covers complex material in an incredibly clear way…I think students who have a weaker background in statistics will learn a lot from the text and students with an advanced background in statistics will look at their analyses in a different way (from the point of planning analyses to actually interpreting results).”

Lesley Williams Reid, Georgia State University

Lesley Williams Reid
Georgia State University
Lesley Williams Reid

“I suspect this book will greatly enhance the teaching and practice of rigorous macro-level comparative analysis. It is a welcome addition to the teaching and training of future comparativists…I like very much the author’s courage in directly assessing and sometimes challenging the existing literature…This book must be taken seriously by all students of comparative politics.  One can learn a great deal from it—it is a “big picture” book, covering well and widely the current state of research and analysis utilizing macro-approaches to the study of comparative politics.”

Thomas Lancaster, Emory University

Thomas Lancaster
Emory University
Thomas Lancaster

“The author explains complex concepts very well. Indeed, I found this far easier to read than most discussions of statistical methods.”

Laura Hatcher, Southern Illinois University

Laura Hatcher
Southern Illinois University
Laura Hatcher

“This is a book of PRIZE WINNING quality…It is also a profoundly original, highly convincing and very innovative attempt to reformulate macro methods to avoid the pitfalls of the clichéd solutions that have filled macro journals with sloppy unconvincing pseudo-scientific analyses for the last twenty years.”

Samuel Cohn, Texas A&M University

Samuel Cohn
Texas A&M University
Samuel Cohn

a good book

Dr Zhidong Zhang
Colg of Education, Univ Of Texas-Brownsville/Tsc
March 4, 2014

The following review regards the book “Methods for quantitative Macro-Comparative Research”, by Salvatore J. Babones.
The book has two big sections: i) “Macro-comparative data structures” which introduces several concepts regarding the logic of quantitative macro comparative research and the use/organization of international data structure; ii) statistical analysis of macro-comparative data. In particular this part introduces to statistical modeling with cross sectional and structured and longitudinal designs. In addition some chapters treat causality, repeated measures and multilevel modeling.
The book is quite discursive, formula/math seems to be avoided to let the reader focus more on concepts than on statistic. In the text there are several figures/schemes which facilitate the reader in the compression of several concepts however, those who benefit most from the book are those who already have the basics of statistic. In fact, readers who are interested in learning how to conduct the analysis, on the subjects described in the text, should refer to other books.
There are some suggestions the Author could consider for future improvements :
1) adding examples which can be conducted using statistical softwares (SPSS/Stata). The examples could guide the reader in experiencing, what it is said in the text. Moreover the reader could became more confident in conducting the analysis.
2) At the beginning of each chapter a brief introduction of what it is going to be found in the following sections could help the reader in familiarizing with the content of the chapter.
3) At the end of each chapter a brief summary could be usefull for reminding the most important concepts met (“what you have learned”).
4) Some exercises could be placed at the end of each chapter to allow the reader a practical revision of what was discussed.

Dr. Gabriele Messina
Research Professor of Public Health
University of Siena

Professor Gabriele Messina
Molecular and Developmental Medicine, University of Siena
January 3, 2014

Excellent book which will be a very useful supplement for our students evaluating comparative research

Ms Marianne Hoeyen
Department of Education, Aarhus University
December 3, 2013
Key features

KEY FEATURES:

  • Offering unique coverage of both data sources and statistical models, this book is accessibly written and does not require mathematics, making it the perfect resource for professionals and students alike.
  • Extensive coverage of causality explores "why we model" (not often covered) rather than "how to model" (found in any textbook), an approach that promotes critical thinking.
  • An extensive, accessible discussion of repeated measures / multilevel models helps readers to understand these highly controversial, poorly understood models.
  • Coverage of when to run which models provides readers with seldom-provided advice.
  • A fascinating final chapter discusses the dynamic link between research and policy, showing how research results directly influence and shape real-life decisions.

Sample Materials & Chapters

Sample Chapter 2

Sample Chapter 7


Sage College Publishing

You can purchase or sample this product on our Sage College Publishing site:

Go To College Site

This title is also available on SAGE Research Methods, the ultimate digital methods library. If your library doesn’t have access, ask your librarian to start a trial.