Skip to:Content
|
Bottom
Cover image for Methods for quantitative macro-comparative research
Title:
Methods for quantitative macro-comparative research
Personal Author:
Publication Information:
California, : Sage Pubn., 2014.
Physical Description:
xxvii, 267 p. : ill. ; 24 cm.
ISBN:
9781412974950

Available:*

Library
Item Barcode
Call Number
Material Type
Item Category 1
Status
Searching...
35000000000965 HA29 B245 2014 Open Access Book Book
Searching...
Searching...
30000010321714 HA29 B245 2014 Open Access Book Book
Searching...

On Order

Summary

Summary

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.


Table of Contents

Prefacep. xi
Introductionp. xv
Macro-Comparative Data Structuresp. xviii
Statistical Analysis of Macro-Comparative Datap. xxi
About the Authorp. xxvii
Part I Macro-Comparative Data Structuresp. 1
1 The Logic of Quantitative Macro-Comparative Researchp. 3
Society as a Complex Systemp. 6
The Micro-Macro Linkp. 1
The Complexity Science Approachp. 8
The Two Systemsp. 10
Levels and Units of Analysisp. 11
The Country as Unitp. 12
Data-Generating Processesp. 15
Gallon and the One-world Problemp. 19
Implications of Compositional Interdependencep. 20
Positive Versus Interpretive Analysisp. 23
2 The International Data Infrastructurep. 27
Sources of Broadly Cross-National Datap. 30
The World Development Indicatorsp. 30
Other Official Sourcesp. 33
NGO and Specialist Sourcesp. 36
Sources of Detailed Rich-Country Datap. 39
Data on Individualsp. 41
Standardized Social Surveysp. 41
Survey and Census Repositoriesp. 45
Emerging Forms of Datap. 46
Internet Metadatap. 47
Satellite Imageryp. 49
Systematic Qualitative Datap. 49
3 Variable Operationalizationp. 51
Transforming Variablesp. 53
Standardizationp. 54
Normalizationp. 56
Operationalizing National Incomep. 59
National Income Conceptsp. 61
Currency Conversion Factorsp. 62
Reference Yearp. 65
Correlational Characteristics of National Income Operationalizationsp. 66
Challenges in Operationalizing Other Economic Variablesp. 66
Inequality and Povertyp. 68
Trade, Investment, and Globalizationp. 70
Concentration, Penetration, and Dependencyp. 71
Operationalization Challenges Relating to Noneconomic Variablesp. 72
4 Cross-National Data Structures and Their Propertiesp. 77
Database Construction With Country Datap. 80
Balanced and Unbalanced Panelsp. 83
Sparse Data and the Treatment of Missing Casesp. 88
Patterns in the Available Datap. 91
A Data Cross-Section of the World Todayp. 94
The Africa-Europe Axisp. 96
Spatial Dependencep. 98
The Time Characteristics of Country Datap. 99
Autocorrelations and Lag Structuresp. 100
Time Points and the Width of a Time Pointp. 102
Part II Statistical Analysis of Macro-Comparative Datap. 105
5 Statistical Modeling With Cross-Sectional Designsp. 107
The Statistical Modeling of Entire Data Populationsp. 108
Error Sampling and the Significance Testing Controversyp. 110
Measurement Error and Regression Attenuationp. 113
Nonrandom Assignment in Data Populationsp. 116
Building and Specifying Cross-Sectional Modelsp. 118
Model Buildingp. 121
National Income as a Contextualizing Control Variablep. 123
Competing and Complementary Controlsp. 126
Triangulation Using Multiple Modelsp. 129
6 Structured and Longitudinal Designs for Establishing Causalityp. 133
Conditions for Causalityp. 135
Structural Equation Modeling as a Template for Causalityp. 136
The Three Principles of Causalityp. 137
Model Designs for Establishing Con-elation, Precedence, and Nonspuriousnessp. 139
Establishing Precedence Using Instrumental Variablesp. 145
Two-Stage Least Squares Regression Modelsp. 147
Structural Equation Models With Reciprocal Effectsp. 149
Establishing Nonspuriousness Using Longitudinal Modelsp. 153
Long-Term Lagged Dependent Variable Modelsp. 154
Difference Modelsp. 157
7 Repeated Measures and Multilevel Modelingp. 161
The Structure of Repeated Measures Datap. 164
The Problem of Nonspherical Errorsp. 164
Correcting for Mean Dependencep. 166
Correcting for Variance Dependencep. 169
Time Series Cross-Sectional Modelsp. 170
Multilevel Modelsp. 174
The Fixed Effects Modelp. 175
The Random Effects Modelp. 177
Making Appropriate Use of Repeated Measures Datap. 180
Time-Invariant Independent Variablesp. 181
Lags and Trendsp. 183
The Slope-Slope Modelp. 185
8 An Interpretive Research and Policy Frameworkp. 187
Empirical Research as Data Descriptionp. 190
Multiple Models as Multiple Lensesp. 191
Viewing Results as Contextually Validp. 195
The Role of Theory in the Search for Causalityp. 198
From p-Values to Grounded Theoryp. 202
Causality, Endogeneity, and Meaningp. 205
The Policy Implications of Research Findingsp. 208
Conclusionp. 213
9 The Political Economy of Quantitative Macro-Comparative Researchp. 215
Industrial Imperatives for Research "Productivity"p. 216
The Challenge From Computational "Social" Sciencep. 219
Five Basic Rules for the Quantitative Analysis of Macro-Comparative Datap. 221
Referencesp. 225
Author Indexp. 241
Subject Indexp. 247
Go to:Top of Page